Overview

Dataset statistics

Number of variables29
Number of observations15480
Missing cells111919
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 MiB
Average record size in memory232.0 B

Variable types

Categorical22
Numeric7

Alerts

Title has a high cardinality: 15071 distinct values High cardinality
Genre has a high cardinality: 1780 distinct values High cardinality
Tags has a high cardinality: 13378 distinct values High cardinality
Languages has a high cardinality: 1438 distinct values High cardinality
Country Availability has a high cardinality: 7530 distinct values High cardinality
Director has a high cardinality: 6746 distinct values High cardinality
Writer has a high cardinality: 9650 distinct values High cardinality
Actors has a high cardinality: 12934 distinct values High cardinality
Boxoffice has a high cardinality: 3836 distinct values High cardinality
Release Date has a high cardinality: 5314 distinct values High cardinality
Netflix Release Date has a high cardinality: 1823 distinct values High cardinality
Production House has a high cardinality: 3814 distinct values High cardinality
Netflix Link has a high cardinality: 15480 distinct values High cardinality
IMDb Link has a high cardinality: 12847 distinct values High cardinality
Summary has a high cardinality: 15449 distinct values High cardinality
Image has a high cardinality: 15479 distinct values High cardinality
Poster has a high cardinality: 11666 distinct values High cardinality
TMDb Trailer has a high cardinality: 7040 distinct values High cardinality
Hidden Gem Score is highly correlated with Metacritic Score and 1 other fieldsHigh correlation
IMDb Score is highly correlated with Rotten Tomatoes Score and 1 other fieldsHigh correlation
Rotten Tomatoes Score is highly correlated with IMDb Score and 1 other fieldsHigh correlation
Metacritic Score is highly correlated with Hidden Gem Score and 4 other fieldsHigh correlation
Awards Received is highly correlated with Metacritic Score and 1 other fieldsHigh correlation
Awards Nominated For is highly correlated with Metacritic Score and 1 other fieldsHigh correlation
IMDb Votes is highly correlated with Hidden Gem ScoreHigh correlation
Hidden Gem Score is highly correlated with Metacritic ScoreHigh correlation
IMDb Score is highly correlated with Rotten Tomatoes Score and 1 other fieldsHigh correlation
Rotten Tomatoes Score is highly correlated with IMDb Score and 1 other fieldsHigh correlation
Metacritic Score is highly correlated with Hidden Gem Score and 2 other fieldsHigh correlation
Awards Received is highly correlated with Awards Nominated ForHigh correlation
Awards Nominated For is highly correlated with Awards ReceivedHigh correlation
Hidden Gem Score is highly correlated with Metacritic Score and 1 other fieldsHigh correlation
IMDb Score is highly correlated with Rotten Tomatoes Score and 1 other fieldsHigh correlation
Rotten Tomatoes Score is highly correlated with IMDb Score and 1 other fieldsHigh correlation
Metacritic Score is highly correlated with Hidden Gem Score and 2 other fieldsHigh correlation
Awards Received is highly correlated with Awards Nominated ForHigh correlation
Awards Nominated For is highly correlated with Awards ReceivedHigh correlation
IMDb Votes is highly correlated with Hidden Gem ScoreHigh correlation
View Rating is highly correlated with Series or MovieHigh correlation
Trailer Site is highly correlated with Series or MovieHigh correlation
Series or Movie is highly correlated with View Rating and 2 other fieldsHigh correlation
Runtime is highly correlated with Series or MovieHigh correlation
Series or Movie is highly correlated with Runtime and 1 other fieldsHigh correlation
Hidden Gem Score is highly correlated with View Rating and 3 other fieldsHigh correlation
Runtime is highly correlated with Series or Movie and 1 other fieldsHigh correlation
View Rating is highly correlated with Series or Movie and 2 other fieldsHigh correlation
IMDb Score is highly correlated with Hidden Gem Score and 2 other fieldsHigh correlation
Rotten Tomatoes Score is highly correlated with Hidden Gem Score and 2 other fieldsHigh correlation
Metacritic Score is highly correlated with Hidden Gem Score and 4 other fieldsHigh correlation
Awards Received is highly correlated with Metacritic Score and 2 other fieldsHigh correlation
Awards Nominated For is highly correlated with Metacritic Score and 2 other fieldsHigh correlation
IMDb Votes is highly correlated with Awards Received and 1 other fieldsHigh correlation
Genre has 1710 (11.0%) missing values Missing
Languages has 1935 (12.5%) missing values Missing
Hidden Gem Score has 2101 (13.6%) missing values Missing
Director has 4708 (30.4%) missing values Missing
Writer has 4330 (28.0%) missing values Missing
Actors has 1925 (12.4%) missing values Missing
View Rating has 7024 (45.4%) missing values Missing
IMDb Score has 2099 (13.6%) missing values Missing
Rotten Tomatoes Score has 9098 (58.8%) missing values Missing
Metacritic Score has 11144 (72.0%) missing values Missing
Awards Received has 9405 (60.8%) missing values Missing
Awards Nominated For has 7819 (50.5%) missing values Missing
Boxoffice has 11473 (74.1%) missing values Missing
Release Date has 2107 (13.6%) missing values Missing
Production House has 10331 (66.7%) missing values Missing
IMDb Link has 2303 (14.9%) missing values Missing
IMDb Votes has 2101 (13.6%) missing values Missing
Poster has 3638 (23.5%) missing values Missing
TMDb Trailer has 8286 (53.5%) missing values Missing
Trailer Site has 8286 (53.5%) missing values Missing
Title is uniformly distributed Uniform
Writer is uniformly distributed Uniform
Actors is uniformly distributed Uniform
Boxoffice is uniformly distributed Uniform
Netflix Link is uniformly distributed Uniform
IMDb Link is uniformly distributed Uniform
Summary is uniformly distributed Uniform
Image is uniformly distributed Uniform
Poster is uniformly distributed Uniform
TMDb Trailer is uniformly distributed Uniform
Netflix Link has unique values Unique

Reproduction

Analysis started2021-10-27 20:49:12.426255
Analysis finished2021-10-27 20:49:34.677533
Duration22.25 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

Title
Categorical

HIGH CARDINALITY
UNIFORM

Distinct15071
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size121.1 KiB
Godzilla
 
4
Kingdom
 
4
Unstoppable
 
3
Alone
 
3
Shameless
 
3
Other values (15066)
15463 

Length

Max length106
Median length15
Mean length17.57383721
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14704 ?
Unique (%)95.0%

Sample

1st rowLets Fight Ghost
2nd rowHOW TO BUILD A GIRL
3rd rowCentigrade
4th rowANNE+
5th rowMoxie

Common Values

ValueCountFrequency (%)
Godzilla4
 
< 0.1%
Kingdom4
 
< 0.1%
Unstoppable3
 
< 0.1%
Alone3
 
< 0.1%
Shameless3
 
< 0.1%
Shaft3
 
< 0.1%
Love3
 
< 0.1%
The Silence3
 
< 0.1%
Tiger3
 
< 0.1%
Limitless3
 
< 0.1%
Other values (15061)15448
99.8%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
the3960
 
8.2%
of1258
 
2.6%
a667
 
1.4%
and599
 
1.2%
in471
 
1.0%
to340
 
0.7%
love332
 
0.7%
2322
 
0.7%
285
 
0.6%
movie278
 
0.6%
Other values (13783)39578
82.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Genre
Categorical

HIGH CARDINALITY
MISSING

Distinct1780
Distinct (%)12.9%
Missing1710
Missing (%)11.0%
Memory size121.1 KiB
Comedy
1186 
Drama
 
1013
Documentary
 
460
Comedy, Drama
 
447
Drama, Romance
 
429
Other values (1775)
10235 

Length

Max length103
Median length18
Mean length20.16180102
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique956 ?
Unique (%)6.9%

Sample

1st rowCrime, Drama, Fantasy, Horror, Romance
2nd rowComedy
3rd rowDrama, Thriller
4th rowDrama
5th rowAnimation, Short, Drama

Common Values

ValueCountFrequency (%)
Comedy1186
 
7.7%
Drama1013
 
6.5%
Documentary460
 
3.0%
Comedy, Drama447
 
2.9%
Drama, Romance429
 
2.8%
Comedy, Romance425
 
2.7%
Comedy, Drama, Romance356
 
2.3%
Crime, Drama, Thriller178
 
1.1%
Action, Crime, Thriller168
 
1.1%
Crime, Drama139
 
0.9%
Other values (1770)8969
57.9%
(Missing)1710
 
11.0%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
drama6359
17.8%
comedy5077
14.2%
action2810
 
7.9%
thriller2739
 
7.7%
romance2445
 
6.8%
crime1932
 
5.4%
adventure1809
 
5.1%
animation1665
 
4.7%
fantasy1594
 
4.5%
family1433
 
4.0%
Other values (18)7845
22.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Tags
Categorical

HIGH CARDINALITY

Distinct13378
Distinct (%)86.8%
Missing67
Missing (%)0.4%
Memory size121.1 KiB
Dramas
 
68
Comedies
 
37
Comedies,Russian Movies
 
29
Stand-up Comedy,Comedies
 
26
Italian Comedies,Comedies,Italian Movies
 
24
Other values (13373)
15229 

Length

Max length653
Median length85
Mean length97.37805748
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12504 ?
Unique (%)81.1%

Sample

1st rowComedy Programmes,Romantic TV Comedies,Horror Programmes,Thai TV Programmes
2nd rowDramas,Comedies,Films Based on Books,British
3rd rowThrillers
4th rowTV Dramas,Romantic TV Dramas,Dutch TV Shows
5th rowSocial Issue Dramas,Teen Movies,Dramas,Comedies,Movies Based on Books

Common Values

ValueCountFrequency (%)
Dramas68
 
0.4%
Comedies37
 
0.2%
Comedies,Russian Movies29
 
0.2%
Stand-up Comedy,Comedies26
 
0.2%
Italian Comedies,Comedies,Italian Movies24
 
0.2%
Comedies,Stand-Up Comedy24
 
0.2%
Comedies,Turkish Movies,Turkish Comedies21
 
0.1%
Kids TV,TV Cartoons,TV Programmes19
 
0.1%
Children & Family Movies19
 
0.1%
Thrillers17
 
0.1%
Other values (13368)15129
97.7%
(Missing)67
 
0.4%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
11218
 
8.0%
tv7684
 
5.5%
based4703
 
3.3%
on4703
 
3.3%
movies3868
 
2.8%
action3637
 
2.6%
sci-fi1878
 
1.3%
dramas1796
 
1.3%
family1624
 
1.2%
films1589
 
1.1%
Other values (6487)97868
69.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Languages
Categorical

HIGH CARDINALITY
MISSING

Distinct1438
Distinct (%)10.6%
Missing1935
Missing (%)12.5%
Memory size121.1 KiB
English
5133 
Japanese
1213 
Korean
 
541
Spanish
 
382
Hindi
 
329
Other values (1433)
5947 

Length

Max length123
Median length7
Mean length10.88755999
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1073 ?
Unique (%)7.9%

Sample

1st rowSwedish, Spanish
2nd rowEnglish
3rd rowEnglish
4th rowTurkish
5th rowEnglish

Common Values

ValueCountFrequency (%)
English5133
33.2%
Japanese1213
 
7.8%
Korean541
 
3.5%
Spanish382
 
2.5%
Hindi329
 
2.1%
English, Spanish267
 
1.7%
French252
 
1.6%
German203
 
1.3%
English, French161
 
1.0%
Mandarin157
 
1.0%
Other values (1428)4907
31.7%
(Missing)1935
 
12.5%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
english8045
41.0%
japanese1671
 
8.5%
spanish1144
 
5.8%
french1057
 
5.4%
korean737
 
3.8%
german692
 
3.5%
hindi539
 
2.7%
mandarin491
 
2.5%
italian484
 
2.5%
russian335
 
1.7%
Other values (186)4446
22.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Series or Movie
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size121.1 KiB
Movie
11697 
Series
3783 

Length

Max length6
Median length5
Mean length5.244379845
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSeries
2nd rowMovie
3rd rowMovie
4th rowSeries
5th rowMovie

Common Values

ValueCountFrequency (%)
Movie11697
75.6%
Series3783
 
24.4%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
movie11697
75.6%
series3783
 
24.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Hidden Gem Score
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct93
Distinct (%)0.7%
Missing2101
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean5.937551387
Minimum0.6
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum0.6
5-th percentile2.1
Q13.8
median6.8
Q37.9
95-th percentile8.6
Maximum9.8
Range9.2
Interquartile range (IQR)4.1

Descriptive statistics

Standard deviation2.250201801
Coefficient of variation (CV)0.3789780761
Kurtosis-1.252594399
Mean5.937551387
Median Absolute Deviation (MAD)1.5
Skewness-0.4291293578
Sum79438.5
Variance5.063408146
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8426
 
2.8%
7.9424
 
2.7%
8.1417
 
2.7%
8.2412
 
2.7%
8.3392
 
2.5%
7.8387
 
2.5%
7.7375
 
2.4%
7.6366
 
2.4%
7.5355
 
2.3%
8.4349
 
2.3%
Other values (83)9476
61.2%
(Missing)2101
 
13.6%
ValueCountFrequency (%)
0.62
 
< 0.1%
0.71
 
< 0.1%
0.84
 
< 0.1%
0.93
 
< 0.1%
16
 
< 0.1%
1.111
 
0.1%
1.229
0.2%
1.322
0.1%
1.441
0.3%
1.545
0.3%
ValueCountFrequency (%)
9.81
 
< 0.1%
9.72
 
< 0.1%
9.64
 
< 0.1%
9.58
 
0.1%
9.47
 
< 0.1%
9.326
 
0.2%
9.231
 
0.2%
9.156
0.4%
966
0.4%
8.9105
0.7%

Country Availability
Categorical

HIGH CARDINALITY

Distinct7530
Distinct (%)48.7%
Missing19
Missing (%)0.1%
Memory size121.1 KiB
Japan
1339 
South Korea
 
715
United Kingdom
 
340
Switzerland,Germany
 
315
United States
 
305
Other values (7525)
12447 

Length

Max length321
Median length37
Mean length112.9306643
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6963 ?
Unique (%)45.0%

Sample

1st rowThailand
2nd rowCanada
3rd rowCanada
4th rowBelgium,Netherlands
5th rowLithuania,Poland,France,Iceland,Italy,Spain,Greece,Czech Republic,Belgium,Portugal,Canada,Hungary,Mexico,Slovakia,Sweden,South Africa,Netherlands,Germany,Thailand,Turkey,Singapore,Romania,Argentina,Israel,Switzerland,Australia,United Kingdom,Brazil,Malaysia,India,Colombia,Hong Kong,Japan,South Korea,United States,Russia

Common Values

ValueCountFrequency (%)
Japan1339
 
8.6%
South Korea715
 
4.6%
United Kingdom340
 
2.2%
Switzerland,Germany315
 
2.0%
United States305
 
2.0%
Poland279
 
1.8%
Italy237
 
1.5%
Canada171
 
1.1%
Czech Republic,Slovakia168
 
1.1%
Thailand162
 
1.0%
Other values (7520)11430
73.8%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
united1592
 
3.2%
south1364
 
2.8%
japan1339
 
2.7%
korea910
 
1.8%
republic,united700
 
1.4%
states651
 
1.3%
hong596
 
1.2%
kong,united469
 
1.0%
kingdom460
 
0.9%
states,malaysia,brazil,netherlands,italy,israel,colombia411
 
0.8%
Other values (17762)40821
82.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Runtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size121.1 KiB
1-2 hour
9121 
< 30 minutes
3996 
> 2 hrs
2028 
30-60 mins
 
334

Length

Max length12
Median length8
Mean length8.944763874
Min length7

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row< 30 minutes
2nd row1-2 hour
3rd row1-2 hour
4th row< 30 minutes
5th row1-2 hour

Common Values

ValueCountFrequency (%)
1-2 hour9121
58.9%
< 30 minutes3996
25.8%
> 2 hrs2028
 
13.1%
30-60 mins334
 
2.2%
(Missing)1
 
< 0.1%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
1-29121
24.7%
hour9121
24.7%
6024
16.3%
303996
10.8%
minutes3996
10.8%
22028
 
5.5%
hrs2028
 
5.5%
30-60334
 
0.9%
mins334
 
0.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Director
Categorical

HIGH CARDINALITY
MISSING

Distinct6746
Distinct (%)62.6%
Missing4708
Missing (%)30.4%
Memory size121.1 KiB
Steven Spielberg
 
28
Raúl Campos, Jan Suter
 
19
Woody Allen
 
18
Johnnie To
 
18
Ridley Scott
 
17
Other values (6741)
10672 

Length

Max length196
Median length13
Mean length15.06052729
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4938 ?
Unique (%)45.8%

Sample

1st rowTomas Alfredson
2nd rowCoky Giedroyc
3rd rowBrendan Walsh
4th rowStephen Irwin
5th rowMez Tharatorn

Common Values

ValueCountFrequency (%)
Steven Spielberg28
 
0.2%
Raúl Campos, Jan Suter19
 
0.1%
Woody Allen18
 
0.1%
Johnnie To18
 
0.1%
Ridley Scott17
 
0.1%
Marcus Raboy17
 
0.1%
Tsutomu Shibayama16
 
0.1%
Pedro Almodóvar16
 
0.1%
Steven Soderbergh16
 
0.1%
Jing Wong16
 
0.1%
Other values (6736)10591
68.4%
(Missing)4708
30.4%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
david212
 
0.8%
john177
 
0.7%
michael148
 
0.6%
lee132
 
0.5%
paul121
 
0.5%
peter118
 
0.5%
james100
 
0.4%
robert90
 
0.4%
steven89
 
0.4%
kim88
 
0.4%
Other values (9088)23695
94.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Writer
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct9650
Distinct (%)86.5%
Missing4330
Missing (%)28.0%
Memory size121.1 KiB
Fujio F. Fujiko
 
17
Woody Allen
 
15
Jing Wong
 
15
Pedro Almodóvar
 
14
George Lucas
 
12
Other values (9645)
11077 

Length

Max length458
Median length27
Mean length31.25901345
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8675 ?
Unique (%)77.8%

Sample

1st rowJohn Ajvide Lindqvist
2nd rowCaitlin Moran
3rd rowBrendan Walsh, Daley Nixon
4th rowPattaranad Bhiboonsawade, Thodsapon Thiptinnakorn, Mez Tharatorn
5th rowIvar Lo-Johansson

Common Values

ValueCountFrequency (%)
Fujio F. Fujiko17
 
0.1%
Woody Allen15
 
0.1%
Jing Wong15
 
0.1%
Pedro Almodóvar14
 
0.1%
George Lucas12
 
0.1%
Charles Chaplin10
 
0.1%
Carlo Vanzina, Enrico Vanzina10
 
0.1%
Luc Besson, Robert Mark Kamen9
 
0.1%
Taylor Sheridan9
 
0.1%
Sang-soo Hong9
 
0.1%
Other values (9640)11030
71.3%
(Missing)4330
 
28.0%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
david457
 
0.9%
john388
 
0.8%
michael364
 
0.7%
paul217
 
0.4%
robert210
 
0.4%
lee207
 
0.4%
mark205
 
0.4%
james185
 
0.4%
peter184
 
0.4%
kim156
 
0.3%
Other values (16098)47933
94.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Actors
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct12934
Distinct (%)95.4%
Missing1925
Missing (%)12.4%
Memory size121.1 KiB
Noriko Ohara, Nobuyo Ôyama, Kaneta Kimotsuki, Michiko Nomura
 
15
Liam Neeson, Ewan McGregor, Natalie Portman, Jake Lloyd
 
12
Inés Sainz, Luis Ernesto Franco, Rafinha Bastos, Tiki Barber
 
9
Priyanka Chopra, Shah Rukh Khan, Isha Koppikar, Arjun Rampal
 
8
Yumi Kakazu, Subaru Kimura, Wasabi Mizuta, Megumi Ohara
 
8
Other values (12929)
13503 

Length

Max length105
Median length57
Mean length55.498045
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12461 ?
Unique (%)91.9%

Sample

1st rowKåre Hedebrant, Per Ragnar, Lina Leandersson, Henrik Dahl
2nd rowPaddy Considine, Cleo, Beanie Feldstein, Dónal Finn
3rd rowGenesis Rodriguez, Vincent Piazza
4th rowVahide Perçin, Gonca Vuslateri, Cansu Dere, Beren Gokyildiz
5th rowRagga Gudrun

Common Values

ValueCountFrequency (%)
Noriko Ohara, Nobuyo Ôyama, Kaneta Kimotsuki, Michiko Nomura15
 
0.1%
Liam Neeson, Ewan McGregor, Natalie Portman, Jake Lloyd12
 
0.1%
Inés Sainz, Luis Ernesto Franco, Rafinha Bastos, Tiki Barber9
 
0.1%
Priyanka Chopra, Shah Rukh Khan, Isha Koppikar, Arjun Rampal8
 
0.1%
Yumi Kakazu, Subaru Kimura, Wasabi Mizuta, Megumi Ohara8
 
0.1%
You, Azusa Babazono, Yoshimi Tokui, Reina Triendl6
 
< 0.1%
Dale Dickey, William Sterchi, Chris Pine, Ben Foster6
 
< 0.1%
Sophia Lillis, Finn Wolfhard, Jaeden Martell, Jeremy Ray Taylor6
 
< 0.1%
Robert Wagner, Michael York, Mike Myers, Heather Graham5
 
< 0.1%
Jeff Dunham5
 
< 0.1%
Other values (12924)13475
87.0%
(Missing)1925
 
12.4%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
lee516
 
0.5%
michael503
 
0.5%
john478
 
0.5%
kim466
 
0.4%
david372
 
0.4%
james309
 
0.3%
de263
 
0.2%
robert255
 
0.2%
tom239
 
0.2%
paul229
 
0.2%
Other values (27609)101980
96.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

View Rating
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct28
Distinct (%)0.3%
Missing7024
Missing (%)45.4%
Memory size121.1 KiB
R
2096 
PG-13
1373 
Not Rated
1320 
TV-MA
1136 
TV-14
798 
Other values (23)
1733 

Length

Max length9
Median length5
Mean length4.353122044
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st rowR
2nd rowR
3rd rowUnrated
4th rowPG-13
5th rowR

Common Values

ValueCountFrequency (%)
R2096
 
13.5%
PG-131373
 
8.9%
Not Rated1320
 
8.5%
TV-MA1136
 
7.3%
TV-14798
 
5.2%
PG657
 
4.2%
TV-PG331
 
2.1%
TV-Y146
 
0.9%
TV-Y7130
 
0.8%
G126
 
0.8%
Other values (18)343
 
2.2%
(Missing)7024
45.4%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
r2096
21.4%
pg-131373
14.0%
not1322
13.5%
rated1322
13.5%
tv-ma1136
11.6%
tv-14798
 
8.2%
pg657
 
6.7%
tv-pg331
 
3.4%
tv-y146
 
1.5%
tv-y7130
 
1.3%
Other values (17)467
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

IMDb Score
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct83
Distinct (%)0.6%
Missing2099
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean6.496054107
Minimum1
Maximum9.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum1
5-th percentile4.4
Q15.8
median6.6
Q37.3
95-th percentile8.2
Maximum9.7
Range8.7
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.14690953
Coefficient of variation (CV)0.1765547994
Kurtosis0.6139261938
Mean6.496054107
Median Absolute Deviation (MAD)0.7
Skewness-0.6039032221
Sum86923.7
Variance1.315401469
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.5508
 
3.3%
6.6507
 
3.3%
6.8504
 
3.3%
6.3498
 
3.2%
6.4493
 
3.2%
7.1490
 
3.2%
7478
 
3.1%
7.2468
 
3.0%
6.7447
 
2.9%
7.3446
 
2.9%
Other values (73)8542
55.2%
(Missing)2099
 
13.6%
ValueCountFrequency (%)
11
 
< 0.1%
1.43
< 0.1%
1.51
 
< 0.1%
1.62
< 0.1%
1.73
< 0.1%
1.93
< 0.1%
24
< 0.1%
2.13
< 0.1%
2.24
< 0.1%
2.34
< 0.1%
ValueCountFrequency (%)
9.71
 
< 0.1%
9.53
 
< 0.1%
9.41
 
< 0.1%
9.32
 
< 0.1%
9.26
 
< 0.1%
9.111
 
0.1%
915
 
0.1%
8.920
 
0.1%
8.827
0.2%
8.754
0.3%

Rotten Tomatoes Score
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct101
Distinct (%)1.6%
Missing9098
Missing (%)58.8%
Infinite0
Infinite (%)0.0%
Mean59.52303353
Minimum0
Maximum100
Zeros76
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum0
5-th percentile12
Q138
median64
Q383
95-th percentile97
Maximum100
Range100
Interquartile range (IQR)45

Descriptive statistics

Standard deviation26.99917321
Coefficient of variation (CV)0.4535920233
Kurtosis-0.9789977126
Mean59.52303353
Median Absolute Deviation (MAD)21
Skewness-0.36328062
Sum379876
Variance728.955354
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100193
 
1.2%
80138
 
0.9%
67133
 
0.9%
50119
 
0.8%
92114
 
0.7%
89111
 
0.7%
83109
 
0.7%
60105
 
0.7%
75104
 
0.7%
91102
 
0.7%
Other values (91)5154
33.3%
(Missing)9098
58.8%
ValueCountFrequency (%)
076
0.5%
14
 
< 0.1%
22
 
< 0.1%
38
 
0.1%
421
 
0.1%
510
 
0.1%
612
 
0.1%
724
 
0.2%
835
0.2%
924
 
0.2%
ValueCountFrequency (%)
100193
1.2%
9920
 
0.1%
9849
 
0.3%
9773
 
0.5%
9676
 
0.5%
9567
 
0.4%
9461
 
0.4%
9393
0.6%
92114
0.7%
91102
0.7%

Metacritic Score
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct95
Distinct (%)2.2%
Missing11144
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean56.81365314
Minimum5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum5
5-th percentile27
Q144
median57
Q370
95-th percentile85
Maximum100
Range95
Interquartile range (IQR)26

Descriptive statistics

Standard deviation17.58254503
Coefficient of variation (CV)0.3094774593
Kurtosis-0.5534176276
Mean56.81365314
Median Absolute Deviation (MAD)13
Skewness-0.1173524093
Sum246344
Variance309.1458897
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51109
 
0.7%
66104
 
0.7%
6899
 
0.6%
6397
 
0.6%
6595
 
0.6%
5594
 
0.6%
6991
 
0.6%
5289
 
0.6%
5888
 
0.6%
5688
 
0.6%
Other values (85)3382
 
21.8%
(Missing)11144
72.0%
ValueCountFrequency (%)
51
 
< 0.1%
61
 
< 0.1%
81
 
< 0.1%
92
< 0.1%
101
 
< 0.1%
113
< 0.1%
123
< 0.1%
134
< 0.1%
142
< 0.1%
154
< 0.1%
ValueCountFrequency (%)
1003
 
< 0.1%
993
 
< 0.1%
982
 
< 0.1%
975
 
< 0.1%
969
0.1%
956
 
< 0.1%
9419
0.1%
936
 
< 0.1%
929
0.1%
9110
0.1%

Awards Received
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct130
Distinct (%)2.1%
Missing9405
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean8.764444444
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q38
95-th percentile34
Maximum300
Range299
Interquartile range (IQR)7

Descriptive statistics

Standard deviation18.31117053
Coefficient of variation (CV)2.089256272
Kurtosis58.12545208
Mean8.764444444
Median Absolute Deviation (MAD)2
Skewness6.32606687
Sum53244
Variance335.2989661
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11692
 
10.9%
2964
 
6.2%
3584
 
3.8%
4463
 
3.0%
5308
 
2.0%
6234
 
1.5%
7195
 
1.3%
8180
 
1.2%
10125
 
0.8%
9124
 
0.8%
Other values (120)1206
 
7.8%
(Missing)9405
60.8%
ValueCountFrequency (%)
11692
10.9%
2964
6.2%
3584
 
3.8%
4463
 
3.0%
5308
 
2.0%
6234
 
1.5%
7195
 
1.3%
8180
 
1.2%
9124
 
0.8%
10125
 
0.8%
ValueCountFrequency (%)
3001
< 0.1%
2511
< 0.1%
2422
< 0.1%
2411
< 0.1%
2391
< 0.1%
2321
< 0.1%
2291
< 0.1%
2101
< 0.1%
1941
< 0.1%
1731
< 0.1%

Awards Nominated For
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct200
Distinct (%)2.6%
Missing7819
Missing (%)50.5%
Infinite0
Infinite (%)0.0%
Mean13.98316147
Minimum1
Maximum386
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q312
95-th percentile58
Maximum386
Range385
Interquartile range (IQR)10

Descriptive statistics

Standard deviation29.82105208
Coefficient of variation (CV)2.132640187
Kurtosis38.0319432
Mean13.98316147
Median Absolute Deviation (MAD)4
Skewness5.38957866
Sum107125
Variance889.2951472
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11525
 
9.9%
2942
 
6.1%
3680
 
4.4%
4518
 
3.3%
5458
 
3.0%
6329
 
2.1%
7327
 
2.1%
8287
 
1.9%
9217
 
1.4%
10187
 
1.2%
Other values (190)2191
 
14.2%
(Missing)7819
50.5%
ValueCountFrequency (%)
11525
9.9%
2942
6.1%
3680
4.4%
4518
 
3.3%
5458
 
3.0%
6329
 
2.1%
7327
 
2.1%
8287
 
1.9%
9217
 
1.4%
10187
 
1.2%
ValueCountFrequency (%)
3861
< 0.1%
3831
< 0.1%
3551
< 0.1%
3451
< 0.1%
3351
< 0.1%
3341
< 0.1%
3171
< 0.1%
3131
< 0.1%
2902
< 0.1%
2811
< 0.1%

Boxoffice
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct3836
Distinct (%)95.7%
Missing11473
Missing (%)74.1%
Memory size121.1 KiB
$474,544,677
 
12
$509
 
9
$2,223,961
 
8
$27,007,844
 
6
$328,828,874
 
6
Other values (3831)
3966 

Length

Max length12
Median length11
Mean length10.05016222
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3713 ?
Unique (%)92.7%

Sample

1st row$2,122,065
2nd row$70,632
3rd row$16,263
4th row$20,578,909
5th row$335,451,311

Common Values

ValueCountFrequency (%)
$474,544,67712
 
0.1%
$5099
 
0.1%
$2,223,9618
 
0.1%
$27,007,8446
 
< 0.1%
$328,828,8746
 
< 0.1%
$206,040,0865
 
< 0.1%
$6,738,0004
 
< 0.1%
$10,4523
 
< 0.1%
$205,881,1543
 
< 0.1%
$202,359,7113
 
< 0.1%
Other values (3826)3948
 
25.5%
(Missing)11473
74.1%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
474,544,67712
 
0.3%
5099
 
0.2%
2,223,9618
 
0.2%
27,007,8446
 
0.1%
328,828,8746
 
0.1%
206,040,0865
 
0.1%
6,738,0004
 
0.1%
90,380,1623
 
0.1%
31,424,0033
 
0.1%
249,0833
 
0.1%
Other values (3826)3948
98.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Release Date
Categorical

HIGH CARDINALITY
MISSING

Distinct5314
Distinct (%)39.7%
Missing2107
Missing (%)13.6%
Memory size121.1 KiB
21 Sep 2018
 
24
12 Oct 2018
 
24
01 Sep 2017
 
24
12 Apr 2019
 
23
04 Aug 2017
 
23
Other values (5309)
13255 

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2692 ?
Unique (%)20.1%

Sample

1st row12 Dec 2008
2nd row08 May 2020
3rd row28 Aug 2020
4th row01 Oct 2016
5th row22 Sep 2011

Common Values

ValueCountFrequency (%)
21 Sep 201824
 
0.2%
12 Oct 201824
 
0.2%
01 Sep 201724
 
0.2%
12 Apr 201923
 
0.1%
04 Aug 201723
 
0.1%
28 Sep 201823
 
0.1%
08 Sep 201723
 
0.1%
06 Apr 201823
 
0.1%
29 Sep 201722
 
0.1%
14 Sep 201822
 
0.1%
Other values (5304)13142
84.9%
(Missing)2107
 
13.6%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
20181495
 
3.7%
20171408
 
3.5%
oct1400
 
3.5%
20191330
 
3.3%
sep1266
 
3.2%
nov1192
 
3.0%
dec1150
 
2.9%
jan1129
 
2.8%
mar1112
 
2.8%
apr1109
 
2.8%
Other values (138)27528
68.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Netflix Release Date
Categorical

HIGH CARDINALITY

Distinct1823
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size121.1 KiB
2015-04-14
2407 
2020-12-12
 
159
2015-09-01
 
154
2018-10-01
 
136
2020-11-27
 
114
Other values (1818)
12510 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique359 ?
Unique (%)2.3%

Sample

1st row2021-03-04
2nd row2021-03-04
3rd row2021-03-04
4th row2021-03-04
5th row2021-03-04

Common Values

ValueCountFrequency (%)
2015-04-142407
 
15.5%
2020-12-12159
 
1.0%
2015-09-01154
 
1.0%
2018-10-01136
 
0.9%
2020-11-27114
 
0.7%
2020-09-05112
 
0.7%
2020-11-2982
 
0.5%
2017-12-2964
 
0.4%
2017-04-0164
 
0.4%
2016-10-0164
 
0.4%
Other values (1813)12124
78.3%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
2015-04-142407
 
15.5%
2020-12-12159
 
1.0%
2015-09-01154
 
1.0%
2018-10-01136
 
0.9%
2020-11-27114
 
0.7%
2020-09-05112
 
0.7%
2020-11-2982
 
0.5%
2017-12-2964
 
0.4%
2017-04-0164
 
0.4%
2016-10-0164
 
0.4%
Other values (1813)12124
78.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Production House
Categorical

HIGH CARDINALITY
MISSING

Distinct3814
Distinct (%)74.1%
Missing10331
Missing (%)66.7%
Memory size121.1 KiB
Netflix
 
82
Paramount Pictures
 
51
Universal Pictures
 
32
Columbia Pictures Corporation
 
30
Working Title Films
 
22
Other values (3809)
4932 

Length

Max length458
Median length28
Mean length35.78772577
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3317 ?
Unique (%)64.4%

Sample

1st rowCanal+, Sandrew Metronome
2nd rowFilm 4, Monumental Pictures, Lionsgate
3rd rowTouchstone Pictures, Spyglass Entertainment
4th rowSvensk Filmindustri, Svenska Filminstitutet
5th rowBron Studios, Creative Wealth Media Finance, DC Comics

Common Values

ValueCountFrequency (%)
Netflix82
 
0.5%
Paramount Pictures51
 
0.3%
Universal Pictures32
 
0.2%
Columbia Pictures Corporation30
 
0.2%
Working Title Films22
 
0.1%
Toho Company Ltd.20
 
0.1%
Warner Brothers19
 
0.1%
TriStar Pictures19
 
0.1%
Warner Brothers/Seven Arts18
 
0.1%
Paramount17
 
0.1%
Other values (3804)4839
31.3%
(Missing)10331
66.7%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
pictures1591
 
6.7%
films1436
 
6.1%
entertainment1218
 
5.1%
productions1012
 
4.3%
film628
 
2.6%
company255
 
1.1%
warner227
 
1.0%
media222
 
0.9%
paramount186
 
0.8%
studios182
 
0.8%
Other values (4113)16744
70.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Netflix Link
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct15480
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size121.1 KiB
https://www.netflix.com/watch/81415947
 
1
https://www.netflix.com/watch/80159732
 
1
https://www.netflix.com/watch/80153272
 
1
https://www.netflix.com/watch/80156916
 
1
https://www.netflix.com/watch/80058398
 
1
Other values (15475)
15475 

Length

Max length38
Median length38
Mean length37.96802326
Min length36

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15480 ?
Unique (%)100.0%

Sample

1st rowhttps://www.netflix.com/watch/81415947
2nd rowhttps://www.netflix.com/watch/81041267
3rd rowhttps://www.netflix.com/watch/81305978
4th rowhttps://www.netflix.com/watch/81336456
5th rowhttps://www.netflix.com/watch/81078393

Common Values

ValueCountFrequency (%)
https://www.netflix.com/watch/814159471
 
< 0.1%
https://www.netflix.com/watch/801597321
 
< 0.1%
https://www.netflix.com/watch/801532721
 
< 0.1%
https://www.netflix.com/watch/801569161
 
< 0.1%
https://www.netflix.com/watch/800583981
 
< 0.1%
https://www.netflix.com/watch/801009371
 
< 0.1%
https://www.netflix.com/watch/801191451
 
< 0.1%
https://www.netflix.com/watch/800818631
 
< 0.1%
https://www.netflix.com/watch/801559061
 
< 0.1%
https://www.netflix.com/watch/800952991
 
< 0.1%
Other values (15470)15470
99.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com/watch/814159471
 
< 0.1%
https://www.netflix.com/watch/801987251
 
< 0.1%
https://www.netflix.com/watch/700230841
 
< 0.1%
https://www.netflix.com/watch/813820651
 
< 0.1%
https://www.netflix.com/watch/813059781
 
< 0.1%
https://www.netflix.com/watch/813364561
 
< 0.1%
https://www.netflix.com/watch/810783931
 
< 0.1%
https://www.netflix.com/watch/813061551
 
< 0.1%
https://www.netflix.com/watch/813075271
 
< 0.1%
https://www.netflix.com/watch/813074821
 
< 0.1%
Other values (15470)15470
99.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

IMDb Link
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct12847
Distinct (%)97.5%
Missing2303
Missing (%)14.9%
Memory size121.1 KiB
https://www.imdb.com/title/tt0120915
 
12
https://www.imdb.com/title/tt5607970
 
9
https://www.imdb.com/title/tt0461936
 
8
https://www.imdb.com/title/tt1396484
 
6
https://www.imdb.com/title/tt2582782
 
6
Other values (12842)
13136 

Length

Max length37
Median length36
Mean length36.07171587
Min length36

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12576 ?
Unique (%)95.4%

Sample

1st rowhttps://www.imdb.com/title/tt1139797
2nd rowhttps://www.imdb.com/title/tt4193072
3rd rowhttps://www.imdb.com/title/tt8945942
4th rowhttps://www.imdb.com/title/tt6132758
5th rowhttps://www.imdb.com/title/tt2023611

Common Values

ValueCountFrequency (%)
https://www.imdb.com/title/tt012091512
 
0.1%
https://www.imdb.com/title/tt56079709
 
0.1%
https://www.imdb.com/title/tt04619368
 
0.1%
https://www.imdb.com/title/tt13964846
 
< 0.1%
https://www.imdb.com/title/tt25827826
 
< 0.1%
https://www.imdb.com/title/tt20956845
 
< 0.1%
https://www.imdb.com/title/tt01456605
 
< 0.1%
https://www.imdb.com/title/tt26311864
 
< 0.1%
https://www.imdb.com/title/tt18773684
 
< 0.1%
https://www.imdb.com/title/tt73351844
 
< 0.1%
Other values (12837)13114
84.7%
(Missing)2303
 
14.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
https://www.imdb.com/title/tt012091512
 
0.1%
https://www.imdb.com/title/tt56079709
 
0.1%
https://www.imdb.com/title/tt04619368
 
0.1%
https://www.imdb.com/title/tt13964846
 
< 0.1%
https://www.imdb.com/title/tt25827826
 
< 0.1%
https://www.imdb.com/title/tt20956845
 
< 0.1%
https://www.imdb.com/title/tt01456605
 
< 0.1%
https://www.imdb.com/title/tt73351844
 
< 0.1%
https://www.imdb.com/title/tt18773684
 
< 0.1%
https://www.imdb.com/title/tt26311864
 
< 0.1%
Other values (12837)13114
99.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Summary
Categorical

HIGH CARDINALITY
UNIFORM

Distinct15449
Distinct (%)99.9%
Missing9
Missing (%)0.1%
Memory size121.1 KiB
A surly septuagenarian gets another chance at her 20s after having her photo snapped at a studio that magically takes 50 years off her life.
 
3
During the late Eastern Han Dynasty, power, intrigue and military ambition collide as rulers, generals and court officials vie for dominance.
 
2
In 1947 Los Angeles, the disappearance of four men, including his own detective, leads a police captain to a cavern where an eerie discovery awaits.
 
2
Young trainer Ash and his new friend Goh become research fellows at Professor Cerises laboratory, traveling all over the world to learn about Pokémon.
 
2
As a woman scours Hyderabad for her missing husband, she becomes entangled in a conspiracy that suggests there’s more to the mystery than meets the eye.
 
2
Other values (15444)
15460 

Length

Max length250
Median length145
Mean length143.2488527
Min length25

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15428 ?
Unique (%)99.7%

Sample

1st rowA med student with a supernatural gift tries to cash in on his abilities by facing off against ghosts, till a wandering spirit brings romance instead.
2nd rowWhen nerdy Johanna moves to London, things get out of hand when she reinvents herself as a bad-mouthed music critic to save her poverty-stricken family.
3rd rowTrapped in a frozen car during a blizzard, a pregnant woman and her husband fight to survive while the temperatures plummet. Inspired by a true story.
4th rowUpon moving into a new place, a 20-something runs into a former flame that triggers memories of past relationships since their split four years ago.
5th rowInspired by her moms rebellious past and a confident new friend, a shy 16-year-old publishes an anonymous zine calling out sexism at her school.

Common Values

ValueCountFrequency (%)
A surly septuagenarian gets another chance at her 20s after having her photo snapped at a studio that magically takes 50 years off her life.3
 
< 0.1%
During the late Eastern Han Dynasty, power, intrigue and military ambition collide as rulers, generals and court officials vie for dominance.2
 
< 0.1%
In 1947 Los Angeles, the disappearance of four men, including his own detective, leads a police captain to a cavern where an eerie discovery awaits.2
 
< 0.1%
Young trainer Ash and his new friend Goh become research fellows at Professor Cerises laboratory, traveling all over the world to learn about Pokémon.2
 
< 0.1%
As a woman scours Hyderabad for her missing husband, she becomes entangled in a conspiracy that suggests there’s more to the mystery than meets the eye.2
 
< 0.1%
As a series of murders hit close to home, a video game designer with post-traumatic stress must confront her demons, or risk becoming their victim.2
 
< 0.1%
Working out is easy when youre having fun! Sing and dance along with Pinkfong, Baby Shark and friends to stay healthy and strong.2
 
< 0.1%
As a blind librarian, dispirited cricketer and desolate psychiatrist each seek retribution and release, their lives overlap under eerie influences.2
 
< 0.1%
After learning of a deadly terrorist threat in London, Alice Racine returns to her job at the CIA only to find the agency may have been compromised.2
 
< 0.1%
In this animated sequel, poachers separate leatherback turtle pals Sammy and Ray, shipping them off for display in an aquarium show.2
 
< 0.1%
Other values (15439)15450
99.8%
(Missing)9
 
0.1%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
a21915
 
5.9%
the14312
 
3.8%
to11710
 
3.1%
and10375
 
2.8%
of9052
 
2.4%
in7586
 
2.0%
his6426
 
1.7%
with4117
 
1.1%
her4013
 
1.1%
an3631
 
1.0%
Other values (28312)280671
75.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

IMDb Votes
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct7886
Distinct (%)58.9%
Missing2101
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean42728.41162
Minimum5
Maximum2354197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size121.1 KiB

Quantile statistics

Minimum5
5-th percentile35
Q1403.5
median2322
Q320890.5
95-th percentile228939.3
Maximum2354197
Range2354192
Interquartile range (IQR)20487

Descriptive statistics

Standard deviation125701.1913
Coefficient of variation (CV)2.941864361
Kurtosis65.0682076
Mean42728.41162
Median Absolute Deviation (MAD)2245
Skewness6.590562469
Sum571663419
Variance1.58007895 × 1010
MonotonicityNot monotonic
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
750
 
0.3%
1038
 
0.2%
836
 
0.2%
930
 
0.2%
627
 
0.2%
1427
 
0.2%
2426
 
0.2%
1525
 
0.2%
523
 
0.1%
3923
 
0.1%
Other values (7876)13074
84.5%
(Missing)2101
 
13.6%
ValueCountFrequency (%)
523
0.1%
627
0.2%
750
0.3%
836
0.2%
930
0.2%
1038
0.2%
1122
0.1%
1220
 
0.1%
1318
 
0.1%
1427
0.2%
ValueCountFrequency (%)
23541971
< 0.1%
23089811
< 0.1%
20729121
< 0.1%
18310042
< 0.1%
18147091
< 0.1%
16843681
< 0.1%
16648651
< 0.1%
16458711
< 0.1%
16252861
< 0.1%
15223061
< 0.1%

Image
Categorical

HIGH CARDINALITY
UNIFORM

Distinct15479
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size121.1 KiB
https://occ-0-37-33.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABTdjKHUl3EC8ls7S_E_bZ5_Bdt49mC8AJYXU93Pdrk5ume73IOFRwrlvxpdJjj9fLAwtyxVtmzgxo2XJ_wUWgGD1uJH9JvxSqcs6fHwD4AWDdf2HKjrevBPObO0.jpg?r=647
 
2
https://occ-0-4708-64.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABcmgLCxN8dNahdY2kgd1hhcL2a6XrE92x24Bx5h6JFUvH5zMrv6lFWl_aWMt33b6DHvkgsUeDx_8Q1rmopwT3fuF8Rq3S1hrkvFf3uzVv2sb3zrtU-LM1Zy1FfrAKD3nKNyA_RQWrmw.jpg?r=cd0
 
1
http://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABSGwADw1yxp0lKCTdWgbz-vh0aR7cIpUrLC22T376-6gIJpiRw8Cd6ChMzHPEq0lb8aznptdcpqarSvWgAnLHECqYUy1Bbe6gJ96HEbMKmNyZx-SiCbzblV3D2Q.jpg?r=176
 
1
https://occ-0-1007-1360.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABUs-fLPuB5GJoa7oNOmPrYyPAAix-1S7LpRwEt1YH0gUiC4ksTAkIyPe_ph8SRuJw8MKN7JpOaYe0uvhgFPuU47Eeg.jpg?r=22f
 
1
http://occ-0-753-1360.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABZHPuEk5silx340bPGjrc4YEz47Z--Jk6F-H_qyIfZeNOk8uMatZz9Oih3jNNI_YsyAX7DkMKe6OxkAN5khF4a0uAQ.jpg?r=909
 
1
Other values (15474)
15474 

Length

Max length305
Median length179
Mean length181.0175711
Min length45

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15478 ?
Unique (%)> 99.9%

Sample

1st rowhttps://occ-0-4708-64.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABcmgLCxN8dNahdY2kgd1hhcL2a6XrE92x24Bx5h6JFUvH5zMrv6lFWl_aWMt33b6DHvkgsUeDx_8Q1rmopwT3fuF8Rq3S1hrkvFf3uzVv2sb3zrtU-LM1Zy1FfrAKD3nKNyA_RQWrmw.jpg?r=cd0
2nd rowhttps://occ-0-1081-999.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABe_fxMSBM1E-sSoszr12SmkI-498sqBWrEyhkchdn4UklQVjdoPS_Hj-NhvgbePvwlDSzMTcrIE0kgiy-zTEU_EaGg.jpg?r=35a
3rd rowhttps://occ-0-1081-999.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABW-fG-2_s3pGsBdbw4nLCWENcRKL2Ngj7Kv5_QQVgZ--GT8eg-BlyJZM9ZaAg5kAYHefo77975PKaTZ3Yza1zLQwgQ.jpg?r=66b
4th rowhttps://occ-0-1489-1490.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABeq3p0f50KPNQTYmozdPUenqXI3bh6Hadry-yMpooR0_Hm2VzUqIzq1V7oihe9ImLxaZC72w9HttdBRoORQT-WVkaA.jpg?r=f82
5th rowhttps://occ-0-4039-1500.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABb72YCHDSHzrB8i5_iG56UFm-qV2bslRyMHIqZ4tmlIpeVtMsqAyUem6JAxXtV4Ec9jlA4EpTdf5tNX2ivyLUwmPy4d3xowFdJE63MPXbWu8kAnc-j9qhAZrmMI.jpg?r=fad

Common Values

ValueCountFrequency (%)
https://occ-0-37-33.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABTdjKHUl3EC8ls7S_E_bZ5_Bdt49mC8AJYXU93Pdrk5ume73IOFRwrlvxpdJjj9fLAwtyxVtmzgxo2XJ_wUWgGD1uJH9JvxSqcs6fHwD4AWDdf2HKjrevBPObO0.jpg?r=6472
 
< 0.1%
https://occ-0-4708-64.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABcmgLCxN8dNahdY2kgd1hhcL2a6XrE92x24Bx5h6JFUvH5zMrv6lFWl_aWMt33b6DHvkgsUeDx_8Q1rmopwT3fuF8Rq3S1hrkvFf3uzVv2sb3zrtU-LM1Zy1FfrAKD3nKNyA_RQWrmw.jpg?r=cd01
 
< 0.1%
http://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABSGwADw1yxp0lKCTdWgbz-vh0aR7cIpUrLC22T376-6gIJpiRw8Cd6ChMzHPEq0lb8aznptdcpqarSvWgAnLHECqYUy1Bbe6gJ96HEbMKmNyZx-SiCbzblV3D2Q.jpg?r=1761
 
< 0.1%
https://occ-0-1007-1360.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABUs-fLPuB5GJoa7oNOmPrYyPAAix-1S7LpRwEt1YH0gUiC4ksTAkIyPe_ph8SRuJw8MKN7JpOaYe0uvhgFPuU47Eeg.jpg?r=22f1
 
< 0.1%
http://occ-0-753-1360.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABZHPuEk5silx340bPGjrc4YEz47Z--Jk6F-H_qyIfZeNOk8uMatZz9Oih3jNNI_YsyAX7DkMKe6OxkAN5khF4a0uAQ.jpg?r=9091
 
< 0.1%
https://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABe8bEkshp64gPwkHTVwtQofiD29Q3JzxaZuDyfslaBaRy_qw2WZJS_dGB0zIrNEkyehws8ff_0QWJe-RRUnurQd4tYzAGkYDgSjYfOZSTIgB5uTBG0EnJFRZ5kE.jpg?r=5311
 
< 0.1%
https://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABalVDDnsficTxZuKZ24XowLBEG2YqcEJolM6QgtHErmJXc8mbMFu14qvH2DZbEz5-8NfMiZ7Q8kdlLK-aB4tLzOlag.jpg?r=f0f1
 
< 0.1%
https://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABQ2oGp8N_CmVIAmsHjhhzuq2Rdx9Qli9em2f58vkpEXjIv9AaB2jnS8n1Feey7ynUmzocUn80zbRoRq5Idsk6ciZ7W2yqY9ru4JUyE_VCoir_aVrX4iMC9Bm09o.jpg?r=d631
 
< 0.1%
https://occ-0-987-116.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABXMHgCtWWN2xXkkvXKT2OQVczs4rkZ8GhXml_56O9H5EzP9PPvLmpitKa_pW2sGPEzvAq_JcofASYQJXn4fc5pEXFex-yT2oJXCFA-toWeseJ3Wc0p5tAEomWgI.jpg?r=a251
 
< 0.1%
https://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABYKUeeTrFto83wzcYCpNCg5uEY-pmDYKmoeNsKFOqxoKru_pLN5q23Nr9XmAUqChqpg1Q6IYTZtJ1c4biD2tryglzQW6cITVg4MI3hxDSbb5eCNbZXhWdTZzprY.jpg?r=0bb1
 
< 0.1%
Other values (15469)15469
99.9%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
https://occ-0-37-33.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabtdjkhul3ec8ls7s_e_bz5_bdt49mc8ajyxu93pdrk5ume73iofrwrlvxpdjjj9flawtyxvtmzgxo2xj_wuwggd1ujh9jvxsqcs6fhwd4awddf2hkjrevbpobo0.jpg?r=6472
 
< 0.1%
https://occ-0-270-2568.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabbyyfgcwhwpfpbfou02ac6uftzypmoueq076h6jlbbzsyp-ou4p1g1pqi7lowblvydgckme0ecwmr8smzxfp0p9uwg.jpg?r=85d1
 
< 0.1%
https://occ-0-993-988.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabzvzi2om7uy20h0qvdfxbdvss4hhq55awlqepaduenfw3mce5boe8a7wbp48wtip71l2jj0l_62ly_di5gsgyit5ma.jpg?r=b291
 
< 0.1%
https://occ-0-2851-41.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabvw0k_2t1gjtj0ysmsoglb6dxx9izzwmykxeyqfky_k8-rfsoxlnaixq2ylws_sutbraicjextuuodoodad-zmv7jw.jpg?r=4b11
 
< 0.1%
https://occ-0-1081-999.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabw-fg-2_s3pgsbdbw4nlcwencrkl2ngj7kv5_qqvgz--gt8eg-blyjzm9zaag5kayhefo77975pkatz3yza1zlqwgq.jpg?r=66b1
 
< 0.1%
https://occ-0-1489-1490.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabeq3p0f50kpnqtymozdpuenqxi3bh6hadry-ympoor0_hm2vzuqizq1v7oihe9imlxazc72w9httdbroorqt-wvkaa.jpg?r=f821
 
< 0.1%
https://occ-0-4039-1500.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabb72ychdshzrb8i5_ig56ufm-qv2bslrymhiqz4tmlipevtmsqayuem6jaxxtv4ec9jla4eptdf5tnx2ivyluwmpy4d3xowfdje63mpxbwu8kanc-j9qhazrmmi.jpg?r=fad1
 
< 0.1%
https://occ-0-2188-64.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabsj6td_whxb4en62ax5ekskml2ltzek5ccbhwbdjrgf6sojb4rtvolhpauweskuoxpiaafxu1qauzdtjguwnq9gsta.jpg?r=e761
 
< 0.1%
https://occ-0-2508-2706.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabsxwh_awvjrqxwanpop86kfpu3kdpqx9rsdyzzghfpialsig2qhkazxm8vhkwr89-olh5xqzihj_5uzwnriady19nq.jpg?r=5611
 
< 0.1%
https://occ-0-2508-2706.1.nflxso.net/dnm/api/v6/evlcitjppcvcry0bzlefb5-qjkc/aaaabuoq8km0vplrak8dpkxjmwy28qjpsdg_wt1ee8bdybmk8x2453s0gquhgvvv-d0ot-yq6c07b31z2s-2messday1cq.jpg?r=6661
 
< 0.1%
Other values (15469)15469
99.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Poster
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct11666
Distinct (%)98.5%
Missing3638
Missing (%)23.5%
Memory size121.1 KiB
https://m.media-amazon.com/images/M/MV5BYTRhNjcwNWQtMGJmMi00NmQyLWE2YzItODVmMTdjNWI0ZDA2XkEyXkFqcGdeQXVyNTAyODkwOQ@@._V1_SX300.jpg
 
11
https://m.media-amazon.com/images/M/MV5BMzAyMWE0MjgtMDVjNS00ZDMyLWE4NjQtNWU2ZDgyYTlmMjdjXkEyXkFqcGdeQXVyNjQ2MjQ5NzM@._V1_SX300.jpg
 
8
https://images-na.ssl-images-amazon.com/images/M/MV5BMjkxMjM5MTkzM15BMl5BanBnXkFtZTgwNDAwODIzMTI@._V1_SX300.jpg
 
6
https://m.media-amazon.com/images/M/MV5BMTg4NDA1OTA5NF5BMl5BanBnXkFtZTgwMDQ2MDM5ODE@._V1_SX300.jpg
 
5
https://m.media-amazon.com/images/M/MV5BZDVkZmI0YzAtNzdjYi00ZjhhLWE1ODEtMWMzMWMzNDA0NmQ4XkEyXkFqcGdeQXVyNzYzODM3Mzg@._V1_SX300.jpg
 
5
Other values (11661)
11807 

Length

Max length190
Median length130
Mean length124.1476102
Min length92

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11531 ?
Unique (%)97.4%

Sample

1st rowhttps://m.media-amazon.com/images/M/MV5BOWM4NTY2NTMtZDZlZS00NTgyLWEzZDMtODE3ZGI1MzI3ZmU5XkEyXkFqcGdeQXVyNzI1NzMxNzM@._V1_SX300.jpg
2nd rowhttps://m.media-amazon.com/images/M/MV5BZGUyN2ZlMjYtZTk2Yy00MWZiLWIyMDktMzFlMmEzOWVlMGNiXkEyXkFqcGdeQXVyMTE1MzI2NzIz._V1_SX300.jpg
3rd rowhttps://m.media-amazon.com/images/M/MV5BODM2MDQ5MjktYTM1ZS00Y2M4LTg0MDAtZjFjZDM1MDQxZGRmXkEyXkFqcGdeQXVyNDA1NDA2NTk@._V1_SX300.jpg
4th rowhttps://m.media-amazon.com/images/M/MV5BNWRkMzdiYjgtOTA0Yi00NjZiLWFjZjMtYThlMTE5MWEwYWU4XkEyXkFqcGdeQXVyODY1MDkwOQ@@._V1_SX300.jpg
5th rowhttps://m.media-amazon.com/images/M/MV5BODYyNWFjODYtYTU3NC00ZmM2LTk3YzEtZDQzZjU0YzZhMTkzXkEyXkFqcGdeQXVyMTE2NzYxNDcz._V1_SX300.jpg

Common Values

ValueCountFrequency (%)
https://m.media-amazon.com/images/M/MV5BYTRhNjcwNWQtMGJmMi00NmQyLWE2YzItODVmMTdjNWI0ZDA2XkEyXkFqcGdeQXVyNTAyODkwOQ@@._V1_SX300.jpg11
 
0.1%
https://m.media-amazon.com/images/M/MV5BMzAyMWE0MjgtMDVjNS00ZDMyLWE4NjQtNWU2ZDgyYTlmMjdjXkEyXkFqcGdeQXVyNjQ2MjQ5NzM@._V1_SX300.jpg8
 
0.1%
https://images-na.ssl-images-amazon.com/images/M/MV5BMjkxMjM5MTkzM15BMl5BanBnXkFtZTgwNDAwODIzMTI@._V1_SX300.jpg6
 
< 0.1%
https://m.media-amazon.com/images/M/MV5BMTg4NDA1OTA5NF5BMl5BanBnXkFtZTgwMDQ2MDM5ODE@._V1_SX300.jpg5
 
< 0.1%
https://m.media-amazon.com/images/M/MV5BZDVkZmI0YzAtNzdjYi00ZjhhLWE1ODEtMWMzMWMzNDA0NmQ4XkEyXkFqcGdeQXVyNzYzODM3Mzg@._V1_SX300.jpg5
 
< 0.1%
https://m.media-amazon.com/images/M/MV5BMjE4OTQyNzM0MV5BMl5BanBnXkFtZTgwOTU0MzgxMDE@._V1_SX300.jpg5
 
< 0.1%
https://m.media-amazon.com/images/M/MV5BMmFkZGQxN2YtODNlYS00MzM5LTk3NjQtNTUxYmQ1YzkwMDhmXkEyXkFqcGdeQXVyMTQxNzMzNDI@._V1_SX300.jpg4
 
< 0.1%
http://ia.media-imdb.com/images/M/MV5BMTc4OTE2MzQxOF5BMl5BanBnXkFtZTYwMTE1MDg4._V1_SX300.jpg3
 
< 0.1%
https://m.media-amazon.com/images/M/MV5BMTU1Mzk2ODEzN15BMl5BanBnXkFtZTgwNDQwMjAxMTI@._V1_SX300.jpg3
 
< 0.1%
http://ia.media-imdb.com/images/M/MV5BMTc5NDE1NzM5N15BMl5BanBnXkFtZTgwOTQxMDY4NjE@._V1_SX300.jpg3
 
< 0.1%
Other values (11656)11789
76.2%
(Missing)3638
 
23.5%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
https://m.media-amazon.com/images/m/mv5bytrhnjcwnwqtmgjmmi00nmqylwe2yzitodvmmtdjnwi0zda2xkeyxkfqcgdeqxvyntayodkwoq@@._v1_sx300.jpg11
 
0.1%
https://m.media-amazon.com/images/m/mv5bmzaymwe0mjgtmdvjns00zdmylwe4njqtnwu2zdgyytlmmjdjxkeyxkfqcgdeqxvynjq2mjq5nzm@._v1_sx300.jpg8
 
0.1%
https://images-na.ssl-images-amazon.com/images/m/mv5bmjkxmjm5mtkzm15bml5banbnxkftztgwndawodizmti@._v1_sx300.jpg6
 
0.1%
https://m.media-amazon.com/images/m/mv5bmtg4nda1ota5nf5bml5banbnxkftztgwmdq2mdm5ode@._v1_sx300.jpg5
 
< 0.1%
https://m.media-amazon.com/images/m/mv5bzdvkzmi0yzatnzdjyi00zjhhlwe1odetmwmzmwmznda0nmq4xkeyxkfqcgdeqxvynzyzodm3mzg@._v1_sx300.jpg5
 
< 0.1%
https://m.media-amazon.com/images/m/mv5bmje4otqynzm0mv5bml5banbnxkftztgwotu0mzgxmde@._v1_sx300.jpg5
 
< 0.1%
https://m.media-amazon.com/images/m/mv5bmmfkzgqxn2ytodnlys00mzm5ltk3njqtntuxymq1yzkwmdhmxkeyxkfqcgdeqxvymtqxnzmzndi@._v1_sx300.jpg4
 
< 0.1%
https://m.media-amazon.com/images/m/mv5bowm4nty2ntmtzdzlzs00ntgylwezzdmtode3zgi1mzi3zmu5xkeyxkfqcgdeqxvynzi1nzmxnzm@._v1_sx300.jpg3
 
< 0.1%
https://m.media-amazon.com/images/m/mv5bzdhizjvlnjctmzq1my00m2qzltkznjutytk0ntdjnzmyzmzjxkeyxkfqcgdeqxvymjmzmdi1odi@._v1_sx300.jpg3
 
< 0.1%
https://images-na.ssl-images-amazon.com/images/m/mv5bymrkngm0yjgtzdrhos00ymm5lwexmjitm2rjoda4njflyza5xkeyxkfqcgdeqxvymzc2mdg1otq@._v1_sx300.jpg3
 
< 0.1%
Other values (11656)11789
99.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

TMDb Trailer
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct7040
Distinct (%)97.9%
Missing8286
Missing (%)53.5%
Memory size121.1 KiB
https://www.youtube.com/watch?v=bD7bpG-zDJQ
 
8
https://www.youtube.com/watch?v=SEJuBrGzPZ4
 
6
https://www.youtube.com/watch?v=_cJRiAfr2PE
 
6
https://www.youtube.com/watch?v=xKJmEC5ieOk
 
5
https://www.youtube.com/watch?v=-Xa08bewnYI
 
5
Other values (7035)
7164 

Length

Max length43
Median length43
Mean length42.92118432
Min length26

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6915 ?
Unique (%)96.1%

Sample

1st rowhttps://www.youtube.com/watch?v=eIbcxPy4okQ
2nd rowhttps://www.youtube.com/watch?v=0RvV7TNUlkQ
3rd rowhttps://www.youtube.com/watch?v=md3CmFLGK6Y
4th rowhttps://www.youtube.com/watch?v=yDB3Ha3vxyc
5th rowhttps://www.youtube.com/watch?v=t433PEQGErc

Common Values

ValueCountFrequency (%)
https://www.youtube.com/watch?v=bD7bpG-zDJQ8
 
0.1%
https://www.youtube.com/watch?v=SEJuBrGzPZ46
 
< 0.1%
https://www.youtube.com/watch?v=_cJRiAfr2PE6
 
< 0.1%
https://www.youtube.com/watch?v=xKJmEC5ieOk5
 
< 0.1%
https://www.youtube.com/watch?v=-Xa08bewnYI5
 
< 0.1%
https://www.youtube.com/watch?v=mYVb4OLk4NQ5
 
< 0.1%
https://www.youtube.com/watch?v=3NQRhE772b04
 
< 0.1%
https://www.youtube.com/watch?v=Q_LfR6mZ5o03
 
< 0.1%
https://www.youtube.com/watch?v=LHrZxG9W3RI3
 
< 0.1%
https://www.youtube.com/watch?v=-JZ_moituIo3
 
< 0.1%
Other values (7030)7146
46.2%
(Missing)8286
53.5%

Length

Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com/watch?v=bd7bpg-zdjq8
 
0.1%
https://www.youtube.com/watch?v=_cjriafr2pe6
 
0.1%
https://www.youtube.com/watch?v=sejubrgzpz46
 
0.1%
https://www.youtube.com/watch?v=xkjmec5ieok5
 
0.1%
https://www.youtube.com/watch?v=-xa08bewnyi5
 
0.1%
https://www.youtube.com/watch?v=myvb4olk4nq5
 
0.1%
https://www.youtube.com/watch?v=3nqrhe772b04
 
0.1%
https://www.youtube.com/watch?v=-jz_moituio3
 
< 0.1%
https://www.youtube.com/watch?v=qd-6d8wo3do3
 
< 0.1%
https://www.youtube.com/watch?v=lhrzxg9w3ri3
 
< 0.1%
Other values (7030)7146
99.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Trailer Site
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing8286
Missing (%)53.5%
Memory size121.1 KiB
YouTube
7159 
Vimeo
 
35

Length

Max length7
Median length7
Mean length6.990269669
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYouTube
2nd rowYouTube
3rd rowYouTube
4th rowYouTube
5th rowYouTube

Common Values

ValueCountFrequency (%)
YouTube7159
46.2%
Vimeo35
 
0.2%
(Missing)8286
53.5%

Length

Histogram of lengths of the category

Pie chart

ValueCountFrequency (%)
youtube7159
99.5%
vimeo35
 
0.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Interactions

Correlations

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

TitleGenreTagsLanguagesSeries or MovieHidden Gem ScoreCountry AvailabilityRuntimeDirectorWriterActorsView RatingIMDb ScoreRotten Tomatoes ScoreMetacritic ScoreAwards ReceivedAwards Nominated ForBoxofficeRelease DateNetflix Release DateProduction HouseNetflix LinkIMDb LinkSummaryIMDb VotesImagePosterTMDb TrailerTrailer Site
0Lets Fight GhostCrime, Drama, Fantasy, Horror, RomanceComedy Programmes,Romantic TV Comedies,Horror Programmes,Thai TV ProgrammesSwedish, SpanishSeries4.3Thailand< 30 minutesTomas AlfredsonJohn Ajvide LindqvistKåre Hedebrant, Per Ragnar, Lina Leandersson, Henrik DahlR7.998.082.074.057.0$2,122,06512 Dec 20082021-03-04Canal+, Sandrew Metronomehttps://www.netflix.com/watch/81415947https://www.imdb.com/title/tt1139797A med student with a supernatural gift tries to cash in on his abilities by facing off against ghosts, till a wandering spirit brings romance instead.205926.0https://occ-0-4708-64.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABcmgLCxN8dNahdY2kgd1hhcL2a6XrE92x24Bx5h6JFUvH5zMrv6lFWl_aWMt33b6DHvkgsUeDx_8Q1rmopwT3fuF8Rq3S1hrkvFf3uzVv2sb3zrtU-LM1Zy1FfrAKD3nKNyA_RQWrmw.jpg?r=cd0https://m.media-amazon.com/images/M/MV5BOWM4NTY2NTMtZDZlZS00NTgyLWEzZDMtODE3ZGI1MzI3ZmU5XkEyXkFqcGdeQXVyNzI1NzMxNzM@._V1_SX300.jpgNaNNaN
1HOW TO BUILD A GIRLComedyDramas,Comedies,Films Based on Books,BritishEnglishMovie7.0Canada1-2 hourCoky GiedroycCaitlin MoranPaddy Considine, Cleo, Beanie Feldstein, Dónal FinnR5.879.069.01.0NaN$70,63208 May 20202021-03-04Film 4, Monumental Pictures, Lionsgatehttps://www.netflix.com/watch/81041267https://www.imdb.com/title/tt4193072When nerdy Johanna moves to London, things get out of hand when she reinvents herself as a bad-mouthed music critic to save her poverty-stricken family.2838.0https://occ-0-1081-999.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABe_fxMSBM1E-sSoszr12SmkI-498sqBWrEyhkchdn4UklQVjdoPS_Hj-NhvgbePvwlDSzMTcrIE0kgiy-zTEU_EaGg.jpg?r=35ahttps://m.media-amazon.com/images/M/MV5BZGUyN2ZlMjYtZTk2Yy00MWZiLWIyMDktMzFlMmEzOWVlMGNiXkEyXkFqcGdeQXVyMTE1MzI2NzIz._V1_SX300.jpghttps://www.youtube.com/watch?v=eIbcxPy4okQYouTube
2CentigradeDrama, ThrillerThrillersEnglishMovie6.4Canada1-2 hourBrendan WalshBrendan Walsh, Daley NixonGenesis Rodriguez, Vincent PiazzaUnrated4.3NaN46.0NaNNaN$16,26328 Aug 20202021-03-04NaNhttps://www.netflix.com/watch/81305978https://www.imdb.com/title/tt8945942Trapped in a frozen car during a blizzard, a pregnant woman and her husband fight to survive while the temperatures plummet. Inspired by a true story.1720.0https://occ-0-1081-999.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABW-fG-2_s3pGsBdbw4nLCWENcRKL2Ngj7Kv5_QQVgZ--GT8eg-BlyJZM9ZaAg5kAYHefo77975PKaTZ3Yza1zLQwgQ.jpg?r=66bhttps://m.media-amazon.com/images/M/MV5BODM2MDQ5MjktYTM1ZS00Y2M4LTg0MDAtZjFjZDM1MDQxZGRmXkEyXkFqcGdeQXVyNDA1NDA2NTk@._V1_SX300.jpghttps://www.youtube.com/watch?v=0RvV7TNUlkQYouTube
3ANNE+DramaTV Dramas,Romantic TV Dramas,Dutch TV ShowsTurkishSeries7.7Belgium,Netherlands< 30 minutesNaNNaNVahide Perçin, Gonca Vuslateri, Cansu Dere, Beren GokyildizNaN6.5NaNNaN1.0NaNNaN01 Oct 20162021-03-04NaNhttps://www.netflix.com/watch/81336456https://www.imdb.com/title/tt6132758Upon moving into a new place, a 20-something runs into a former flame that triggers memories of past relationships since their split four years ago.1147.0https://occ-0-1489-1490.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABeq3p0f50KPNQTYmozdPUenqXI3bh6Hadry-yMpooR0_Hm2VzUqIzq1V7oihe9ImLxaZC72w9HttdBRoORQT-WVkaA.jpg?r=f82https://m.media-amazon.com/images/M/MV5BNWRkMzdiYjgtOTA0Yi00NjZiLWFjZjMtYThlMTE5MWEwYWU4XkEyXkFqcGdeQXVyODY1MDkwOQ@@._V1_SX300.jpgNaNNaN
4MoxieAnimation, Short, DramaSocial Issue Dramas,Teen Movies,Dramas,Comedies,Movies Based on BooksEnglishMovie8.1Lithuania,Poland,France,Iceland,Italy,Spain,Greece,Czech Republic,Belgium,Portugal,Canada,Hungary,Mexico,Slovakia,Sweden,South Africa,Netherlands,Germany,Thailand,Turkey,Singapore,Romania,Argentina,Israel,Switzerland,Australia,United Kingdom,Brazil,Malaysia,India,Colombia,Hong Kong,Japan,South Korea,United States,Russia1-2 hourStephen IrwinNaNRagga GudrunNaN6.3NaNNaNNaN4.0NaN22 Sep 20112021-03-04NaNhttps://www.netflix.com/watch/81078393https://www.imdb.com/title/tt2023611Inspired by her moms rebellious past and a confident new friend, a shy 16-year-old publishes an anonymous zine calling out sexism at her school.63.0https://occ-0-4039-1500.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABb72YCHDSHzrB8i5_iG56UFm-qV2bslRyMHIqZ4tmlIpeVtMsqAyUem6JAxXtV4Ec9jlA4EpTdf5tNX2ivyLUwmPy4d3xowFdJE63MPXbWu8kAnc-j9qhAZrmMI.jpg?r=fadhttps://m.media-amazon.com/images/M/MV5BODYyNWFjODYtYTU3NC00ZmM2LTk3YzEtZDQzZjU0YzZhMTkzXkEyXkFqcGdeQXVyMTE2NzYxNDcz._V1_SX300.jpgNaNNaN
5The Con-HeartistComedy, RomanceRomantic Comedies,Comedies,Romantic Films,Thai Comedies,Thai FilmsThaiMovie8.6Thailand> 2 hrsMez TharatornPattaranad Bhiboonsawade, Thodsapon Thiptinnakorn, Mez TharatornThiti Mahayotaruk, Nadech Kugimiya, Kathaleeya McIntosh, Pimchanok LeuwisetpaiboonNaN7.4NaNNaNNaNNaNNaN03 Dec 20202021-03-03NaNhttps://www.netflix.com/watch/81306155https://www.imdb.com/title/tt13393728After her ex-boyfriend cons her out of a large sum of money, a former bank employee tricks a scam artist into helping her swindle him in retaliation.131.0https://occ-0-2188-64.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABSj6td_whxb4en62Ax5EKSKMl2lTzEK5CcBhwBdjRgF6SOJb4RtVoLhPAUWEskuOxPiaafxU1qauZDTJguwNQ9GstA.jpg?r=e76https://m.media-amazon.com/images/M/MV5BODAzOGZmNjUtMTIyMC00NGU1LTg5MTMtZWY4MDdiZjI0NGEwXkEyXkFqcGdeQXVyNzEyMTA5MTU@._V1_SX300.jpghttps://www.youtube.com/watch?v=md3CmFLGK6YYouTube
6Gleboka wodaDramaTV Dramas,Polish TV Shows,Social Issue TV DramasPolishSeries8.7Poland< 30 minutesNaNNaNMarcin Dorocinski, Piotr Nowak, Julia Kijowska, Katarzyna MaciagNaN7.5NaNNaN2.04.0NaN14 Jun 20112021-03-03NaNhttps://www.netflix.com/watch/81307527https://www.imdb.com/title/tt2300049A group of social welfare workers led by their new director tries to provide necessary aid to people struggling with various problems.47.0https://occ-0-2508-2706.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABSxWH_aWvJrqXWANpOp86kFpU3kdpqx9RsdYZZGHfpIalSig2QHKaZXm8vhKWr89-OLh5XqzIHj_5UzwNriADy19NQ.jpg?r=561https://m.media-amazon.com/images/M/MV5BMTc0NzZiYTYtMTQyNy00Mjg0LTk1NzMtMTljMjI4ZmM4ZjFmXkEyXkFqcGdeQXVyMTc4MzI2NQ@@._V1_SX300.jpgNaNNaN
7InstynktCrimeTV Dramas,Crime TV Dramas,Polish TV ShowsPolishSeries6.9Poland< 30 minutesNaNNaNPawel Królikowski, Szymon Bobrowski, Danuta Stenka, Piotr GlowackiNaN3.9NaNNaNNaNNaNNaN03 Mar 20112021-03-03NaNhttps://www.netflix.com/watch/81307482https://www.imdb.com/title/tt1973421An enigmatic commissioner joins the Warsaw Police, where her unconventional investigation methods unsettle the officers in the homicide department.107.0https://occ-0-2508-2706.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABUOq8KM0VPlrak8DpkXjMWY28qjpsdG_WT1ee8BDyBmk8X2453s0gQuHGVvV-D0OT-yq6C07b31Z2s-2MesSDaY1CQ.jpg?r=666https://m.media-amazon.com/images/M/MV5BZWYyYWQxZGUtYTNjMy00OGVhLTk4MTktZDgwOTdiOGZmMDA1L2ltYWdlXkEyXkFqcGdeQXVyMTc4MzI2NQ@@._V1_SX300.jpgNaNNaN
8Only a MotherDramaSocial Issue Dramas,Dramas,Movies Based on Books,Period Pieces,Swedish MoviesSwedishMovie8.3Lithuania,Poland,France,Italy,Spain,Greece,Belgium,Portugal,Netherlands,Germany,Switzerland,United Kingdom,Iceland,Czech Republic1-2 hourAlf SjöbergIvar Lo-JohanssonUlf Palme, Ragnar Falck, Hugo Björne, Eva DahlbeckNaN6.7NaNNaN2.01.0NaN31 Oct 19492021-03-03NaNhttps://www.netflix.com/watch/81382068https://www.imdb.com/title/tt0041155An unhappily married farm worker struggling to care for her children reflects on her lost youth and the scandalous moment that cost her true love.88.0https://occ-0-2851-41.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABdpOFktQ4Z3klQEU2XQc9NWompf70CHEGLPIeBdCGGLDhvy1Mqly5552DUYR5-5M77STCj8rPvCbXltOcTj53olEzA.jpg?r=c84https://m.media-amazon.com/images/M/MV5BMjVmMzA5OWYtNTFlMy00ZDBlLTg4NDUtM2NjYjFhMGYwZjBkXkEyXkFqcGdeQXVyNzQxNDExNTU@._V1_SX300.jpgNaNNaN
9SnowrollerComedySports Movies,Sports Comedies,Comedies,Swedish MoviesSwedish, English, German, NorwegianMovie5.3Lithuania,Poland,France,Italy,Spain,Greece,Czech Republic,Belgium,Portugal,Hungary,Slovakia,Netherlands,Germany,Romania,Switzerland,United Kingdom,Iceland1-2 hourLasse ÅbergLasse Åberg, Bo JonssonJon Skolmen, Cecilia Walton, Lasse Åberg, Eva MillbergNaN6.6NaNNaNNaNNaNNaN04 Oct 19852021-03-03NaNhttps://www.netflix.com/watch/81382187https://www.imdb.com/title/tt0090115Two friends take a ski trip to the Alps, where they enjoy the outdoors and try to charm two women also on vacation.5926.0https://occ-0-2851-41.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABQoql2u62H3BqwAhwJWTF-F0QIaG7dmZiMx8WDff2YUSCX-Sgo072F5HPosZbBJTcYQBjNACBHurAbB40rPQxWBrzQ.jpg?r=667https://m.media-amazon.com/images/M/MV5BZDY2NGFkMjUtOGQxOS00M2E0LWE1MmYtNDYzOGNiNWI0NmJkXkEyXkFqcGdeQXVyMTQzMjU1NjE@._V1_SX300.jpgNaNNaN

Last rows

TitleGenreTagsLanguagesSeries or MovieHidden Gem ScoreCountry AvailabilityRuntimeDirectorWriterActorsView RatingIMDb ScoreRotten Tomatoes ScoreMetacritic ScoreAwards ReceivedAwards Nominated ForBoxofficeRelease DateNetflix Release DateProduction HouseNetflix LinkIMDb LinkSummaryIMDb VotesImagePosterTMDb TrailerTrailer Site
15470Jochem Myjer: Yeeehaa!NaNStand-up Comedy,International Movies,ComediesNaNMovieNaNBelgium1-2 hourNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70281218NaNJoin comedian and musician Jochem Myjer for a roller-coaster ride of wacky dances, spirited trivia games and sublime impersonations of famous people.NaNhttp://occ-0-768-769.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABV4d4qe6Y-_hy-qWvcdlYizxWXKhupmJcgT_JI8LeW-I9VsXjjc_BZhdvy4furR0taY0LypZ5dNxu27qOAQnfzi1xA.jpg?r=fedNaNNaNNaN
15471DreamWorks Short StoriesNaNTV Comedies,Kids TV,TV Programmes,TV Cartoons,Family Watch Together TVNaNSeriesNaNUnited Kingdom,France,Switzerland,Belgium,Netherlands,Germany< 30 minutesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70259782NaNDreamWorkss coolest characters star in this collection of shorts that finds B.O.B. planning a breakout, zombie carrots on the attack and more.NaNhttps://occ-0-2773-2774.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABfaddRM5S_tPZouVxOQ8BsNnDV-J_W3p2QqBKpIsMjygFIY_UDYNgCic5PofIgM6vEWacbIzza1-Q8ZDRxNa9NGKfA.jpg?r=5b4NaNNaNNaN
15472DreamWorks Shrek StoriesNaNTV Comedies,Kids TV,TV Programmes,Animal Tales,TV Cartoons,TV Shows Based on Books,Family Watch Together TVNaNSeriesNaNBelgium,United Kingdom,France,Switzerland,Netherlands,Germany< 30 minutesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70259783NaNShrek celebrates a busy Christmas and a spooky Halloween, Puss in Boots is captured by soldiers, and the kingdom hosts a singing competition.NaNhttps://occ-0-2773-2774.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABaXUdtjsLm-qWVTvFXvXhShbVSPd1pt2IBX_FcIhpEGPs-IdT8_uMZtYEcxLPqYLicbwO4W_5itME84Iz--Im0bBcg.jpg?r=b1bNaNNaNNaN
15473Daniel Arends: BlessuretijdComedyStand-up Comedy,International Movies,ComediesDutchMovie8.8Belgium1-2 hourDoesjka van HoogdalemDaniël ArendsDaniël ArendsNaN7.8NaNNaNNaNNaNNaN13 Jan 20122015-04-14NaNhttps://www.netflix.com/watch/70281233NaNIn his third show, Daniël Arends argues that good deeds are a form of self interest, and evil deeds are a hobby.174.0http://occ-0-768-769.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABfaXNjUOW0ImkindVrKUsLj6_pGyZqgruElfokzYYslHo3Ixvj_csRujDog1rkI2TJ8TS8FbO2oCkKaOTqiiz7vYcQ.jpg?r=120NaNNaNNaN
15474Nijntje and VriendjesNaNKids TV,TV Programmes,Dutch TV Shows,TV Shows Based on BooksNaNSeriesNaNBelgium,Netherlands< 30 minutesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70282153NaNDick Brunas classic childrens stories get a new twist in this stop-motion animated series about Miffy the bunny and her friends.NaNhttps://occ-0-768-769.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABY5C71RCNbVt7hOmI4rscRydaog34XC7zzZnbesd3Sj8Q-KI-cZYqvMtO7eJXbv3KEOBdQSXsyxu7Fw1EmSTHXyKPg.jpg?r=d9aNaNNaNNaN
15475K-POP Extreme SurvivalNaNTV Dramas,TV Programmes,TV Comedies,Romantic TV Comedies,Music & Musicals,Korean TV ShowsNaNSeriesNaNSouth Korea,Argentina,United Kingdom,Australia,Switzerland,France,Spain,Iceland,India,Lithuania,Russia,Czech Republic,Romania,Singapore,United States,Canada,Mexico,Hong Kong,South Africa,Belgium,Hungary,Greece,Slovakia,Turkey,Malaysia,Brazil,Israel,Colombia< 30 minutesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/80031595NaNSeung Yeon decides to chase her dream of becoming a K-pop star and audition for a popular group. Theres only one catch: Its a boy band.NaNhttps://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABQviZS2b2JMOgU8Brpj04HonopFETV3XdiEJk72dhMK_ZgI8drDPi58GeLVGuj4ikroPJqwin3bxvST4t3Q9p6c9_Q.jpg?r=59aNaNNaNNaN
15476DreamWorks Shreks Swamp StoriesNaNAnimal Tales,Family Comedies,Family Adventures,Children & Family Films,Films for ages 8 to 10,Comedies,Films based on childrens books,Films for ages 5 to 7,Comedy Programmes,Action & Adventure Programmes,TV Cartoons,Kids&#39; TV,TV Programmes Based on Books,Family Watch Together TVNaNSeriesNaNRussia,Hong Kong,Hungary,Australia,South Korea,Poland,Lithuania,Japan,Romania,Argentina,Spain,Portugal,Czech Republic,Canada,South Africa,Singapore,United States,Greece,Slovakia,Thailand,Turkey,Malaysia,Brazil,Italy,Iceland,Israel,India,Mexico,Colombia< 30 minutesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70242630NaNShrek celebrates Halloween, Puss in Boots is captured by soldiers, and the gang participates in a kingdom-wide singing competition.NaNhttps://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABck2o1jCpt_mzvzdFREbMb9t5Uh85V9tzaHwTehAPcyqklM5Qwgl1t1yznUNV7DPBzIYQTXgn5OelxIXzP7Iwd7cog.jpg?r=8c4NaNNaNNaN
15477DreamWorks Happy Holidays from MadagascarAnimation, Comedy, FamilyTV Comedies,Kids TV,Animal Tales,TV Cartoons,TV Programmes,Romantic Favorites,Family Watch Together TVEnglishSeries8.4Belgium,Switzerland,United States,Germany,United Kingdom,France,India,Russia,Greece,Slovakia,Singapore,Poland,Czech Republic,Lithuania,Hong Kong,Romania,South Africa,Australia,Spain,Iceland,Portugal,South Korea,Japan,Thailand,Hungary,Turkey,Mexico,Canada,Argentina,Malaysia,Brazil,Netherlands,Italy,Israel,Colombia< 30 minutesNaNNaNJung Hyun KimNaN6.8NaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70259784NaNMadagascar goes wild with holiday spirit in this set of Valentines Day and Christmas-themed tales featuring everyones favorite animal characters.71.0https://occ-0-2773-2774.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABZw5kYV3oBd71eWvQXoSm5BufEIzAa3uVfNeu1eHhGiP1R4tUX_lf5-DRNZbfBSS54Kc62LH3wsi2Ic9nYOr5PsvTA.jpg?r=9b7NaNNaNNaN
15478DreamWorks Holiday ClassicsAnimation, Comedy, FamilyTV Comedies,Kids TV,TV Cartoons,TV Programmes,Family Watch Together TVEnglishSeries8.2Belgium,Switzerland,Germany,Argentina,United Kingdom,France,Poland,Slovakia,Czech Republic,Lithuania,Romania,Greece,India,Russia,South Africa,Singapore,Hong Kong,Australia,Spain,Iceland,South Korea,Japan,Mexico,Canada,Thailand,Hungary,Portugal,Turkey,United States,Malaysia,Brazil,Netherlands,Italy,Israel,Colombia< 30 minutesNaNNaNNaNUnrated6.4NaNNaNNaNNaNNaNNaN2015-04-14Foxhttps://www.netflix.com/watch/70221348NaNJoin your DreamWorks friends for these four holiday specials, featuring Shrek and Donkey, Hiccup and Toothless, and the wacky animals from Madagascar.82.0https://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABYJ7VZV8ZC5k9vYP9wgVF7zmGotI27xLHGsbNdV7a7f1cBAK5wpRgLiHu72tRt-CYt9K0S04d_apfQ1AP83nsEvqWw.jpg?r=461NaNNaNNaN
15479DreamWorks Kung Fu Panda Awesome SecretsAnimation, Action, Comedy, FamilyTV Comedies,Kids TV,Animal Tales,TV Cartoons,TV Programmes,Action & Adventure Programmes,Family Watch Together TVEnglishSeries8.1Belgium,Switzerland,Germany,United Kingdom,France,India,Russia,Greece,South Korea,Slovakia,Singapore,Poland,Czech Republic,Lithuania,Hong Kong,Romania,South Africa,Australia,Spain,Iceland,Portugal,Japan,Thailand,United States,Hungary,Turkey,Canada,Argentina,Mexico,Malaysia,Brazil,Netherlands,Italy,Israel,Colombia< 30 minutesNaNNaNNaNTV-PG6.2NaNNaNNaNNaNNaNNaN2015-04-14NaNhttps://www.netflix.com/watch/70241791NaNIn this pair of adventures, Po tells the story of how masters Thundering Rhino, Storming Ox and Croc met and takes on Shifus biggest challenge yet.17.0https://occ-0-2851-38.1.nflxso.net/dnm/api/v6/evlCitJPPCVCry0BZlEFb5-QjKc/AAAABUB5x0Ln3__-FRjQ7fCQiGT6PD2ltD2pyQluXR9SqF5lg_wBRBWxf_n-C9xM1TnBXZkQS8JM4lQVa6MlG-JYCH9fUA.jpg?r=cfcNaNNaNNaN